White Light Interferometry for Quantitative Surface Characterization in Ion Sputtering Experiments

White light interferometry (WLI) can be used to obtain surface morphology information on dimensional scale of millimeters with lateral resolution as good as ~1 {\mu}m and depth resolution down to 1 nm. By performing true three-dimensional imaging of sample surfaces, the WLI technique enables accurate quantitative characterization of the geometry of surface features and compares favorably to scanning electron and atomic force microscopies by avoiding some of their drawbacks. In this paper, results of using the WLI imaging technique to characterize the products of ion sputtering experiments are reported. With a few figures, several example applications of the WLI method are illustrated when used for (i) sputtering yield measurements and time-to-depth conversion, (ii) optimizing ion beam current density profiles, the shapes of sputtered craters, and multiple ion beam superposition and (iii) quantitative characterization of surfaces processed with ions. In particular, for sputter depth profiling experiments of 25Mg, 44Ca and 53Cr ion implants in Si (implantation energy of 1 keV per nucleon), the depth calibration of the measured depth profile curves determined by the WLI method appeared to be self-consistent with TRIM simulations for such projectile-matrix systems. In addition, high depth resolution of the WLI method is demonstrated for a case of a Genesis solar wind Si collector surface processed by gas cluster ion beam: a 12.5 nm layer was removed from the processed surface, while the transition length between the processed and untreated areas was 150 {\mu}m.Comment: Applied Surface Science, accepted: 7 pages and 8 figure

Comparison Of Three Transient Models For Slab Heating/Cooling Systems

Radiant floor heating and cooling systems can be beneficial in various applications such as heating or cooling buildings and in infrastructure applications such as de-icing of bridges and roads as well as snow melting. Such systems usually include a significant amount of thermal mass, thus providing energy flexibility in buildings. Models of embedded-tube radiant systems are therefore useful to predict their behavior (rate of heat transfer and outlet heat-transfer fluid temperature), which can be used for the development of predictive control strategies and optimal control algorithms. As a result, a comparison of different models is conducted in this paper. The TRNSYS simulation software provides three different ways of modeling radiant floor systems (Type 56, Type 653, and Type 993), which are compared in this paper with one another in order to assess their accuracy and limitations. Each approach is compared with measurements from an experimental set-up in a controlled environmental chamber. This paper aims at: (i) evaluating the appropriate model resolution for embedded-tube radiant floor systems, (ii) validating experimentally the three aforementioned TRNSYS types (which have been validated qualitatively only), and (iii) providing a mathematical explanation of Type 993 (whose description is still unavailable to TRNSYS users). A sensitivity analysis is also performed to estimate the impact of the different types’ parameters

Helimeric porphyrinoids: Stereostructure and chiral resolution of meso -tetraarylmorpholinochlorins

The synthesis and chiral resolution of free-base and Ni(II) complexes of a number of derivatives of meso-tetraphenylmorpholinochlorins, with and without direct β-carbon-to-o-phenyl linkages to the flanking phenyl groups, is described. The morpholinochlorins, a class of stable chlorin analogues, were synthesized in two to three steps from meso-tetraphenylporphyrin. The conformations and the relative stereostructures of a variety of free-base and Ni(II) complexes of these morpholinochlorins were elucidated by X-ray diffractometry. Steric and stereoelectronic arguments explain the relative stereoarray of the morpholino-substituents, which differ in the free-base and Ni(II) complexes, and in the monoalkoxy, β-carbon-to-o-phenyl linked morpholinochlorins, and the dialkoxy derivatives. The Ni(II) complexes were all found to be severely ruffled whereas the free-base chromophores are more planar. As a result of the helimeric distortion of their porphyrinoid chromophores, the ruffled macrocycles possess a stable inherent element of chirality. Most significantly, resolution of the racemic mixtures was achieved, both by classical methods via diastereomers and by HPLC on a chiral phase. Full CD spectra were recorded and modeled using quantum-chemical computational methods, permitting, for the first time, an assignment of the absolute configurations of the chromophores. The report expands the range of known pyrrole-modified porphyrins. Beyond this, it introduces large chiral porphyrinoid π-systems that exist in the form of two enantiomeric, stereochemically stable helimers that can be resolved. This forms the basis for possible future applications, for example, in molecular-recognition systems or in materials with chiroptic properties. © 2011 American Chemical Society

Strategies for cancer treatment based on photonic nanomedicine

Traditional cancer treatments, such as surgery, radiotherapy, and chemotherapy, are still the most effective clinical practice options. However, these treatments may display moderate to severe side effects caused by their low temporal or spatial resolution. In this sense, photonic nanomedicine therapies have been arising as an alternative to traditional cancer treatments since they display more control of temporal and spatial resolution, thereby yielding fewer side effects. In this work, we reviewed the challenge of current cancer treatments, using the PubMed and Web of Science database, focusing on the advances of three prominent therapies approached by photonic nanomedicine: (i) photothermal therapy; (ii) photodynamic therapy; (iii) photoresponsive drug delivery systems. These photonic nanomedicines act on the cancer cells through different mechanisms, such as hyperthermic effect and delivery of chemotherapeutics and species that cause oxidative stress. Furthermore, we covered the recent advances in materials science applied in photonic nanomedicine, highlighting the main classes of materials used in each therapy, their applications in the context of cancer treatment, as well as their advantages, limitations, and future perspectives. Finally, although some photonic nanomedicines are undergoing clinical trials, their effectiveness in cancer treatment have already been highlighted by pre-clinical studies

High Resolution PET with 250 micrometer LSO Detectors and Adaptive Zoom

There have been impressive improvements in the performance of small-animal positron emission tomography (PET) systems since their first development in the mid 1990s, both in terms of spatial resolution and sensitivity, which have directly contributed to the increasing adoption of this technology for a wide range of biomedical applications. Nonetheless, current systems still are largely dominated by the size of the scintillator elements used in the detector. Our research predicts that developing scintillator arrays with an element size of 250 {micro}m or smaller will lead to an image resolution of 500 {micro}m when using 18F- or 64Cu-labeled radiotracers, giving a factor of 4-8 improvement in volumetric resolution over the highest resolution research systems currently in existence. This proposal had two main objectives: (i) To develop and evaluate much higher resolution and efficiency scintillator arrays that can be used in the future as the basis for detectors in a small-animal PET scanner where the spatial resolution is dominated by decay and interaction physics rather than detector size. (ii) To optimize one such high resolution, high sensitivity detector and adaptively integrate it into the existing microPET II small animal PET scanner as a 'zoom-in' detector that provides higher spatial resolution and sensitivity in a limited region close to the detector face. The knowledge gained from this project will provide valuable information for building future PET systems with a complete ring of very high-resolution detector arrays and also lay the foundations for utilizing high-resolution detectors in combination with existing PET systems for localized high-resolution imaging

Monitoring rice agropractices in North Africa: a comparison of MODIS and Sentinel-1 results

Agro-monitoring systems need up-to-date information on where, when and how much a crop is cultivated, in particular in developing countries and for food security reasons. Such information can be derived from remote sensing imagery with fast revisiting cycles. In the past, only time series of optical moderate resolution data such as HVRR, SPOT-Vegetation and MODIS provided the necessary high temporal resolution for this kind of applications. These datasets have been successfully used for agro-monitoring activities and to perform retrospective and trend analysis. Due to their moderate to coarse spatial resolution (~ 250 – 1000 m) their applications are limited however to regional to continental scales. In this context, the advent of the Sentinel sensors opens new opportunities, since they provide time series of satellite imagery with decametric spatial resolution and revisit times of 5 days. Studies that fully exploit Sentinel imagery for crop monitoring are therefore needed to assess their potential contribution for i) performing high resolution crop-monitoring activities and, ii) extending time series of information derived from archive coarse resolution imagery with the aim of performing analyses of temporal trends over a reasonably long time span. This contribution presents a comparison of MODIS or Sentinel1 time series for detection (cultivated area and number of seasons) and seasonal dynamics’ analysis (sowing, harvesting and flowering dates) for irrigated rice cultivation in the Senegal River Valley (SRV)for the 2016 dry and wet rice seasons. MODIS time series analysis exploited the PhenoRice algorithm (Boschetti et al., 2017), a rule-based algorithm specifically designed for rice detection and seasonal dynamics monitoring and based on the use of time series of TERRA and AQUA 250 m resolution 16-day Composite Vegetation Indexes (MODIS products MOD13Q1 and MYD13Q1). The SAR data analysis was instead based on analysis of Sentinel-1A time series acquired over the study area from January to December 2016. In particular, the RICEscape software was used for analysing the SAR backscatter (0) temporal profiles both in the VV and in the VH polarization, to define a set of rules allowing to properly identify rice cultivated areas. The algorithm mostly exploits SAR data, although cloud free Landsat-8 Optical images were used to crosscheck and complement the information derived from SAR. This approach was applied to generate rice crop area and Start of Season (SOS) maps for both the dry (sowing in February – April) and the wet (sowing in September – November) rice seasons. Results showed a strong consistency between the thematic maps derived from the two data sources. We observed that, although the rice-classified area is rather different due to the large difference in spatial resolution, the main spatial patterns of estimated sowing dates and crop intensity are quite similar. A comparison between the average values of MODIS and SAR estimated dates after aggregation on a 2x2 km regular grid shows a strong correlation between the sowing dates derived from Sentinel-1 and MODIS data, for both the dry and the wet season of 2016. The comparability of MODIS and Sentinel results is encouraging for the development of innovative services for characterization and monitoring of crop systems. Such systems could in fact exploit both the sufficiently long MODIS time series to characterize the main characteristics of crop systems and their recent evolution, as well as the innovative Sentinel-1 time series for monitoring of present-day and future conditions

Structure and Dynamics of Macromolecular Assemblies from Electron Microscopy Maps

Electron microscopy (EM) and electron tomography (ET) have found extensive application to probe structural and dynamic properties of macromolecular assemblies. As an important complementary to X-ray and NMR in atomic structural determination, EM has reached a milestone resolution of 2.2Å, enough for understanding atomic interactions, interpreting mechanism of functions, and for structure-based drug design. This work describes approaches to derive structural information from EM/ET images and methods to study dynamics of macromolecular systems using EM/ET images as starting or ending targets. For low-resolution EM/ET maps, X-ray or NMR atomic structures of molecular components are needed to reduce the number of degrees of uncertainty. Depending on the resolution of EM/ET maps and the conformational differences from the X-ray or NMR structures, either rigid fitting or flexible fitting is used to obtain atomic structures. To illustrate the procedures of the atomic structure derivation, this work describes the core-weighted grid-threading Monte Carlo (CW-GTMC) rigid fitting and the map-restrained self-guided Langevin dynamics (MapSGLD) flexible fitting methods. Their applications are highlighted with four examples: architecture of an icosahedral pyruvate dehydrogenase complex, dynamics of a group II chaperonin, high-resolution structure of the cell-permeant inhibitor phenylethyl β-D-thiogalactopyranoside, and the mechanism of kinesin walking on microtube

Neural Implicit Representations for Physical Parameter Inference from a Single Video

Neural networks have recently been used to analyze diverse physical systems and to identify the underlying dynamics. While existing methods achieve impressive results, they are limited by their strong demand for training data and their weak generalization abilities to out-of-distribution data. To overcome these limitations, in this work we propose to combine neural implicit representations for appearance modeling with neural ordinary differential equations (ODEs) for modelling physical phenomena to obtain a dynamic scene representation that can be identified directly from visual observations. Our proposed model combines several unique advantages: (i) Contrary to existing approaches that require large training datasets, we are able to identify physical parameters from only a single video. (ii) The use of neural implicit representations enables the processing of high-resolution videos and the synthesis of photo-realistic images. (iii) The embedded neural ODE has a known parametric form that allows for the identification of interpretable physical parameters, and (iv) long-term prediction in state space. (v) Furthermore, the photo-realistic rendering of novel scenes with modified physical parameters becomes possible.Comment: Published in IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 202